CODEWITHSUNDEEP
rmatrixoptimization
user1819274
user1819274

Reputation: 59

Optimizing all values in a matrix

I'm trying to write code to efficiently solve for all values in a matrix based on an optimization. I'm trying to find the value of x that minimizes the equation:

(x - (1 / ((1 / x) - sqrt(1 / x))))^2

I wrote some code that accomplishes this task, but it isn't pretty (nor is it fast).

mSS <- function(x)
{
   #Sum of squares for X and the transformation
  (x - (1 / ((1 / test_mat[rows, cols]) - sqrt(1 / x))))^2  
}

n = 151
m = 50000
test_mat  = matrix(rnorm(n * m, mean = 0, sd = 1), n, m)
trans_mat = matrix(data = NA, n, m)

#Go through each row/col position in array, find value that minimizes mSS function
for (cols in 1:ncol(test_mat)) {
  for (rows in 1:nrow(test_mat)) {
    trans_mat[rows, cols] = optimize(mSS, c(0, 3))$minimum
  }
}

I'm mentally stuck trying to figure out the best approach for making this go faster. I was thinking maybe using apply with some custom functions might be the route, but I'm having difficulty figuring out a workable solution. Any pointers in the right direction would be appreciated.

Upvotes: 1

Views: 109

Answers (1)

Sandipan Dey
Sandipan Dey

Reputation: 23101

Try this:

mSS<-function(x, a)
{
  #Sum of squares for X and the transformation
  (x-(1/((1/a)-sqrt(1/x))))^2  
}
y <- as.numeric(test_mat)
ty <- sapply(y, function(x) optimize(mSS,c(0,3),a=x)$minimum)
trans_mat <- matrix(ty, nrow=nrow(test_mat))

Upvotes: 2

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